Patents
Literature
Patsnap Eureka AI that helps you search prior art, draft patents, and assess FTO risks, powered by patent and scientific literature data.

3 results about "Speech therapy" patented technology

Speech therapy learning machine

ActiveCN309876433SLearning machineAcoustics
1. The name of the design product: speech correction learning machine. 2. The use of the design product: for speech correction of the hearing-impaired. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: perspective view.
Owner:于尚宇 +4

Systems and methods for monitoring functional neuroplasticity

ActiveUS12683025B2Occupational therapyMedicine
Systems and methods for monitoring neuroplasticity within at least one region of interest of a brain of a subject are disclosed. The method includes transforming at least one time sequence of signals indicative of neural activity into a summary parameter indicative of plasticity pulses. The method further includes evaluating the summary parameter with respect to one or more threshold values to obtain a determination of neuroplasticity within at least one region of interest of the subject. The method may be used to evaluate the efficacy of a neuroactive therapy, such as a neuroactive medication, a physical therapy, an occupational therapy or a speech therapy. The summary parameter obtained using the disclosed method may be displayed to a subject as a biofeedback during a neurotherapy.
Owner:WASHINGTON UNIV IN SAINT LOUIS

Speech therapy system and method therefor

PCT designated stageWO2026035406A1Stammering correctionSpeech recognitionEngineeringAcoustics
A speech therapy system and method therefor are disclosed. The system includes graduated speaking exercise modules and a computer system including a processor and a memory. The modules are arranged sequentially and are collectively configured to provide graduated speaking exercises, or GSEs, of increasing conversational realism for a stuttering user. The processor executes the app and the modules, and each of the modules create an associated GSE that defines a different state of the app. When the app is in a current state defined by a current GSE, the app obtains or determines a fluency metric from user speech or from a user fluency self-rating. When the metric meets an upper fluency threshold of the current GSE, the app transitions to a next app state defined by a next GSE, and the app can conclude that the user is fluent if the upper threshold is met for a final GSE.
Owner:FLUENCYAI LLC